Description

Full Stack AI Engineering is an AI application development course published by Towards AI Online Academy. This course provides a comprehensive roadmap for building AI applications. The course covers all aspects of AI development, from data collection and model training to deployment and integration on web and mobile platforms. Learners will gain hands-on experience designing scalable AI systems, implementing machine learning models, and creating interactive applications that use AI to solve real-world problems.

This course explores the complete AI engineering workflow, including data preprocessing, feature engineering, and training machine learning and deep learning models. Students will learn to integrate models into full-stack applications using backend frameworks, APIs, and frontend interfaces. The curriculum covers deployment strategies, cloud services, and monitoring of AI systems to ensure reliability and scalability. It also emphasizes best practices in model optimization, versioning, and ethical use of AI. By the end, learners will be able to design, build, and deploy fully functional AI applications that combine advanced models with robust, user-friendly interfaces.

What you will learn in Full Stack AI Engineering:

• Build your advanced LLM project
• Earn the role of LLM Developer
• Become one of the top LLM developers needed for the widespread adoption of GenAI in companies
• And…

Course specifications

Publisher: Towards AI
Instructors: Louis-François
Language: English
Level: Introductory to Advanced
Number of Lessons: 26
Duration: 2 hours and 25 minutes

Course topics

Full Stack AI Engineering Prerequisites

Intermediate Python knowledge

Basic knowledge of GitHub

Necessary libraries for code implementations

Compatible device to setup a coding environment

At least 50 hours to gain the full benefit of the course

Pictures

Full Stack AI Engineering introduction video

Installation guide

After Extract, watch with your favorite Player.

Subtitle: None

Quality: 1080p

Downloadly link

Download Part 1 – 1 GB

Download Part 2 – 111 MB

Rapidgator link

Download Part 1 – 1 GB

Download Part 2 – 111 MB

File password (s): www.downloadly.ir

Size

1.1 GB